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Analysis Of The Impact Of Covid-19 On Key Demographic Indicators In Romania And Moldova Using Econometric Modeling

Author

Listed:
  • PARTACHI Ion

    (Academy of Economic Studies of Moldova (University))

  • MIJA Simion

    (Academy of Economic Studies of Moldova (University))

  • HERTELIU Claudiu

    (Bucharest University of Economic Studies)

Abstract

The complexity of the impact of the COVID-19 pandemic crisis remains a challenging subject to define and estimate. In this paper, we will reflect on the impact from the perspective of demographic indicators, considering how the crisis has affected family well-being, especially in relation to dependence on remittances. We will also address the problematic aspects caused by the crisis on social and economic mobility, as well as the perception of state responses to the pandemic, from a comparative perspective. This includes examining the support interventions provided to families, the public policy measures adopted, and the responses of public health systems in Moldova and Romania. Econometric analysis of these effects offers a detailed understanding of how COVID-19 has influenced demographic dynamics in both countries, facilitating the development of policies better suited to the post-pandemic context.

Suggested Citation

  • PARTACHI Ion & MIJA Simion & HERTELIU Claudiu, 2024. "Analysis Of The Impact Of Covid-19 On Key Demographic Indicators In Romania And Moldova Using Econometric Modeling," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 76(4), pages 132-139, December.
    • Handle: RePEc:blg:reveco:v:76:y:2024:i:4:p:132-139
    DOI: 10.56043/reveco-2024-0038
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    References listed on IDEAS

    as
    1. Sims, Christopher A & Zha, Tao, 1998. "Bayesian Methods for Dynamic Multivariate Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 949-968, November.
    2. James H. Stock & Mark W. Watson, 2001. "Vector Autoregressions," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 101-115, Fall.
    3. James H. Stock & Mark W. Watson, 1988. "A Probability Model of The Coincident Economic Indicators," NBER Working Papers 2772, National Bureau of Economic Research, Inc.
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    More about this item

    Keywords

    econometric analysis; demographic dynamics; COVID-19;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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